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Detecting LHC Neutrinos at Surface Level
No full textThe first direct detection of neutrinos at the LHC not only marks the beginning of a novel collider neutrino program at CERN but also motivates considering additional neutrino detectors to fully exploit the associated physics potential. We investigate the feasibility and physics potential of neutrino experiments located at the surface-level. A topographic desk study was performed to identify all points at which the LHC's neutrino beams exit the earth. The closest location lies about 9 km east of the CMS interaction point, at the bottom of Lake Geneva. Several detectors to be placed at this location are considered, including a water Cherenkov detector and an emulsion detector. The detector concepts are introduced, and projections for their contribution to the LHC forward neutrino program and searches for dark sector particles are presented. However, the dilution of the neutrino flux over distance reduces the neutrino yield significantly, limiting the physics potential of surface-level detectors compared to ones closer to the interaction point, including the proposed FPF
Towards the first high-Q treatments for 800 MHz 5-cell elliptical cavities
No full textHigh-efficiency, high-velocity, sub-GHz elliptical superconducting RF cavities are a critical enabling technology for multiple upcoming accelerator development projects such as for the Powerful Energy Recovery Linac for Experiments (PERLE), and for the Future Circular Collider s (FCC) Booster, and future realizations of its Collider ring. The ambitious quality factor and gradient requirements of these applications require strong SRF R&D; programs aimed at developing and optimizing advanced surface processing techniques for 800 MHz cavities. We report the initiation of the 800 MHz R&D; program at Fermilab, with the aim of developing high-performance cavities compatible with PERLE and FCC applications
LHC upgrade and physics
No full textThis presentation summaries major ATLAS and CMS upgrade projects for the HL-LHC, together with the expected physics object performance and projected physics sensitivities. This is for a plenary presentation at the IAS 2025 conference in Hong Kong (13-17 Jan 2025)
Visit by Professor Stefanie Reese, Rector, University of Siegen, Germany
No full textVisit by Professor Stefanie Reese, Rector, University of Siegen, Federal Republic of German
Neutrino Experiments at the Large Hadron Collider
No full textThe proton-proton collisions at the Large Hadron Collider (LHC) produce an intense, high-energy beam of neutrinos of all flavors, collimated in the forward direction. Recently two dedicated neutrino experiments, FASER and SND@LHC, have started operating to take advantage of the TeV energy LHC neutrino beam, with first results released in 2023 and further results released in 2024. The first detection of neutrinos produced at a particle collider opens up a new avenue of research, allowing to study the highest energy neutrinos produced in a controlled laboratory environment, with an associated broad and rich physics program. Neutrino measurements at the LHC will provide important contributions to QCD, neutrino and BSM physics, with impactful implications for astro-particle physics. This review article summarizes the physics motivation, status and plans of, present and future neutrino experiments at the LHC
PICOSEC Micromegas precise-timing detectors: development towards large-area application and integration
No full textPICOSEC Micromegas (MM) is a precise timing gaseous detector based on a Cherenkov radiator coupled with a semi-transparent photocathode and an MM amplifying structure. The detectorconceptwas successfully demonstrated through a single-channel prototype, achieving sub-25 ps time resolution with Minimum Ionizing Particles (MIPs). A series of studies followed, aimed at developing robust, large-area, and scalable detectors with high time resolution, complemented by specialized fast-response readout electronics. This work presents recent advancements towards large-area resistive PICOSEC MM, including 10 × 10 cm area prototypes and a 20 × 20 cm prototype, which features the jointing of four photocathodes. The time resolution of these detector prototypes was tested during the test beam, achieved a timing performance of around 25 ps for individual pads in MIPs. Meanwhile, customized electronics have been developed dedicated to the high-precision time measurement of the large-area PICOSEC MM. The performance of the entire system was evaluated during the test beam, demonstrating its capability for large-area integration. These advancements highlight the potential of PICOSEC MM to meet the stringent requirements of future particle physics experiments.PICOSEC Micromegas (MM) is a precise timing gaseous detector based on a Cherenkov radiator coupled with a semi-transparent photocathode and an MM amplifying structure. The detector conceprt was successfully demonstrated through a single-channel prototype, achieving sub-25 ps time resolution with Minimum Ionizing Particles (MIPs). A series of studies followed, aimed at developing robust, large-area, and scalable detectors with high time resolution, complemented by specialized fast-response readout electronics. This work presents recent advancements towards large-area resistive PICOSEC MM, including 10 10 area prototypes and a 20 20 prototype, which features the jointing of four photocathodes. The time resolution of these detector prototypes was tested during the test beam, achieved a timing performance of around 25 ps for individual pads in MIPs. Meanwhile, customized electronics have been developed dedicated to the high-precision time measurement of the large-area PICOSEC MM. The performance of the entire system was evaluated during the test beam, demonstrating its capability for large-area integration. These advancements highlight the potential of PICOSEC MM to meet the stringent requirements of future particle physics experiments
Machine learning for real-time muon identification of the LHCb experiment at CERN
No full textThe LHCb experiment at CERN has been recently upgraded to collect data at a luminosity for the Run 3 (2022), employing a real-time event reconstruction of the 40 MHz proton-proton collisions generated by the Large Hadron Collider. This generates an output data flow of 5 Tb/s, which is the largest in high-energy physics to date. To face this challenge, the LHCb collaboration has developed a full software trigger in two levels: HLT1 (running on GPUs) and HLT2 (running on CPUs) to filter events that are saved in the storage (disks and magnetic tapes). Among the trigger tasks, the reconstruction and identification of muons is of paramount importance for the success of the LHCb physics program in the Run 3 and beyond. This is achieved by developing, optimising and testing fast and efficient algorithms. The purpose of the work described in this thesis is to enhance the performance of muon identification by means of machine learning techniques. In Chapter 1, an overview of the LHCb experiment and its muon identification procedure are provided. In Chapter 2, machine learning is introduced focusing on the models and tools that are relevant for this project. Chapter 3 describes the data analysis and feature engineering, while Chapter 4 concerns the training of the models and the evaluation of their performance
